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Deviations from uniform power law scaling in nonstationary time seriesA classic problem in physics is the analysis of highly nonstationary time series that typically exhibit long-range correlations. Here we test the hypothesis that the scaling properties of the dynamics of healthy physiological systems are more stable than those of pathological systems by studying beat-to-beat fluctuations in the human heart rate. We develop techniques based on the Fano factor and Allan factor functions, as well as on detrended fluctuation analysis, for quantifying deviations from uniform power-law scaling in nonstationary time series. By analyzing extremely long data sets of up to N = 10(5) beats for 11 healthy subjects, we find that the fluctuations in the heart rate scale approximately uniformly over several temporal orders of magnitude. By contrast, we find that in data sets of comparable length for 14 subjects with heart disease, the fluctuations grow erratically, indicating a loss of scaling stability.
Document ID
Document Type
Reprint (Version printed in journal)
External Source(s)
Viswanathan, G. M.
(Boston University Massachusetts 02215, United States)
Peng, C. K.
Stanley, H. E.
Goldberger, A. L.
Date Acquired
August 21, 2013
Publication Date
January 1, 1997
Publication Information
Publication: Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
Volume: 55
Issue: 1
ISSN: 1063-651X
Subject Category
Life Sciences (General)
Funding Number(s)
Distribution Limits
Non-NASA Center
NASA Discipline Cardiopulmonary
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